Assessing internal carotid artery stenosis: Diagnostic Value of photon-counting detector CT angiography compared to Doppler ultrasound

To evaluate the diagnostic accuracy of photon-counting detector CT angiography (PCD-CTA) for grading internal carotid artery (ICA) stenosis compared to color Doppler ultrasonography (CDUS).

In this study, patients underwent both contrast-enhanced PCD-CTA and CDUS within six months. Four board-certified radiologists graded ICA stenosis using the North American Symptomatic Carotid Endarterectomy Trial (NASCET) criteria (grades 1-5) through visual and measurement-based methods from PCD-CTA. CDUS measurements served as the reference standard. Measurements were analyzed via Spearman's correlation and Fleiss's Kappa for inter-reader reliability. Image quality was assessed visually and through coefficient of variation measurements. A simulated intention-to-treat analysis compared that potentially require treatment (stenoses ≥ 70 % - grade 4 or higher) with stenosis < 70 %.

A total of 31 patients (mean age 70.5 ± 10.2, 48.4 % female) and 60 ICAs were analyzed. CDUS identified 12/60 (20 %) cases of clinically significant stenosis. PCD-CTA stenosis measurements showed strong agreement with CDUS, with a mean difference of 5.85 % ± 9.8 % and a significant correlation (Spearman's rho = 0.951, p < 0.001). Inter-reader reliability was moderate (Fleiss's kappa values 0.56 for visual, 0.53 for measurement-based grading). In the intention-to-treat analysis, PCD-CTA visual assessments had 93.8 % sensitivity and 93.8 % specificity for detecting clinically significant stenosis, while quantitative CT measurement-based grading showed 75 % sensitivity and 96.9 % specificity. Misclassifications occurred in cases with severe calcifications. Image quality was excellent or good in 96 % of cases.

PCD-CTA demonstrated high diagnostic accuracy with moderate inter-reader reliability for ICA stenosis grading, comparable to CDUS. However, misclassification due to calcified stenosis suggests the need for further improvements in imaging and analysis.